Redefining Cloud Migration in the AI Era

Sachin Kotian
Head Architecture, Customer Advisory - SAS India

Sachin Kotian of SAS India commends that the cloud landscape is entering a more mature phase, going beyond simply moving workloads. “Cloud environments will increasingly serve as the foundation for real-time decision making, automation, and innovation at scale, with organizations placing greater emphasis on interoperability, governance, and responsible AI. Cloud-native analytics platforms, embedded intelligence, and AI-driven automation will help enterprises respond faster to change, improve operational efficiency, and create competitive advantage in an increasingly digital economy.”

IS MIGRATING TO CLOUD A DAUNTING TASK?

As pointed out by many, the biggest challenge to migrating workloads to cloud will be to maintain business continuity. “Legacy environments often contain complex dependencies, large data volumes, and processes that cannot tolerate disruption. A phased approach, combining data validation, application regression testing, parallel operations, and rollback planning, reduces risk and helps organizations modernize while maintaining operational stability,” says Sachin.

Sachin also adds that security and compliance should be embedded throughout the migration lifecycle. “Organizations need clear governance covering data ownership, access controls, encryption, identity management, audit requirements, and continuous monitoring. It begins with understanding what data exists, where it resides, and the regulations that apply to it. This assessment helps determine the right deployment model. Ongoing compliance monitoring, automated policy enforcement, regular security reviews, and visibility into data usage help organizations meet regulatory requirements while protecting customer trust.”